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Meeting 2022 TMS Annual Meeting & Exhibition
Symposium REWAS 2022: Automation and Digitalization for Advanced Manufacturing
Presentation Title Determining the Bubble Dynamics of a Top Submerged Lance Smelter
Author(s) Avinash Kandalam, Markus Reinmöller, Michael Stelter, Markus A Reuter, Alexandros Charitos
On-Site Speaker (Planned) Avinash Kandalam
Abstract Scope Top Submerged Lance (TSL) smelter is widely used in non-ferrous metallurgy to extract various primary and secondary materials. The technology has found wide application with regard to copper, lead and zinc, nickel tin, while applications concerning iron and municipal solid waste treatment have been reported. As of 2019, there are about 66 operating TSL plants globally. By controlling the air/fuel ratio (i.e. by lambda value), the TSL can be operated under oxidizing/reducing/inert conditions. The bubble dynamics play a crucial role in determining the reaction kinetics, splashing, turbulence, sloshing as well as the refractory and lance wear. This paper shows the efforts to determine the bubble dynamics in a cold TSL-model using acoustic measurements, lance motion system, and high-speed photography. The results show a correlation between bubble dynamics with respect to varying lance submersion depths, bath properties (varying viscosities and densities, i.e. glycerol/water mixtures), and lance flow rates (i.e. airflow).
Proceedings Inclusion? Planned:
Keywords Extraction and Processing, Pyrometallurgy, Process Technology

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

AI/Data Mining in Materials Manufacturing
Audio Signal Processing for Quantitative Moulding Material Regeneration
Computational Methodology to Simulate Pyrometallurgical Processes in a Secondary Lead Furnace
Determining the Bubble Dynamics of a Top Submerged Lance Smelter
Development of Virtual Die Casting Simulator for Workforce Development
Digitalization for Advanced Manufacturing through Simulation, Visualization and Machine Learning
Digitalizing the Circular Economy (CE): From Reactor Simulation to System Models of the CE
Evolution of Process Models to Digital Twins
Factors to Consider when Designing Aluminium Alloys for Increased Scrap Usage
NOW ON-DEMAND ONLY - An Automated Recycling Process of End-of-life Lithium-ion Batteries Enhanced by Online Sensing and Machine Learning Techniques
Refractory Lifetime Prediction in Industrial Processes with Artificial Intelligence
Steel Production Efficiency Improvements by Digitalization

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